Browsing by Author "Baravalle, L.D."

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    Searching for extragalactic sources in the VISTA variables in the Via láctea survey
    (Institute of Physics Publishing, 2018) Baravalle, L.D.; Alonso, M.V.; Castellón, J.L.N.; Beamín, J.C.; Minniti, D.
    We search for extragalactic sources in the VISTA Variables in the Vía Láctea survey that are hidden by the Galaxy. Herein, we describe our photometric procedure to find and characterize extragalactic objects using a combination of SExtractor and PSFEx. It was applied in two tiles of the survey: d010 and d115, without previous extragalactic IR detections, in order to obtain photometric parameters of the detected sources. The adopted criteria to define extragalactic candidates include CLASS-STAR < 0.3; 1.0 < R1 2 < 5.0 arcsec; 2.1 < C < 5; and F > 0.002 and the colors: 0.5 < (J-Ks) < 2.0 mag; 0.0 < (J-H) < 1.0 mag; 0.0 < (H-Ks) < 2.0 mag and (J-H) + 0.9 (H-Ks) > 0.44 mag. We detected 345 and 185 extragalactic candidates in the d010 and d115 tiles, respectively. All of them were visually inspected and confirmed to be galaxies. In general, they are small and more circular objects, due to the near-IR sensitivity to select more compact objects with higher surface brightness. The procedure will be used to identify extragalactic objects in other tiles of the VVV disk, which will allow us to study the distribution of galaxies and filaments hidden by the Milky Way.
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    The VVV near-IR galaxy catalogue in a Northern part of the Galactic disc
    (Oxford University Press, 2023-09-01) Daza-Perilla, I.V.; Sgró, M.A.; Baravalle, L.D.; Alonso, M.V.; Villalon, C.; Lares, M.; Soto, M.; Castellón, J. L. Nilo; Valotto, C.; Cortes, P. Marchant; Minniti, D.; Hempel, M.
    The automated identification of extragalactic objects in large surveys provides reliable and reproducible samples of galaxies in less time than procedures involving human interaction. However, regions near the Galactic disc are more challenging due to the dust extinction. We present the methodology for the automatic classification of galaxies and non-galaxies at low Galactic latitude regions using both images and photometric and morphological near-IR data from the VISTA Variables in the Vía Láctea eXtended (VVVX) survey. Using the VVV NIR Galaxy Catalogue (VVV NIRGC), we analyse by statistical methods the most relevant features for galaxy identification. This catalogue was used to train a convolutional neural network with image data and an XGBoost model with both photometric and morphological data and then to generate a data set of extragalactic candidates. This allows us to derive probability catalogues used to analyse the completeness and purity as a function of the configuration parameters and to explore the best combinations of the models. As a test case, we apply this methodology to the Northern disc region of the VVVX survey, obtaining 172 396 extragalactic candidates with probabilities of being galaxies. We analyse the performance of our methodology in the VVV disc, reaching an F1-score of 0.67, a 65 per cent purity, and a 69 per cent completeness. We present the VVV NIRGC: Northern part of the Galactic disc comprising 1003 new galaxies, with probabilities greater than 0.6 for either model, with visual inspection and with only two previously identified galaxies. In the future, we intend to apply this methodology to other areas of the VVVX survey. © 2023 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.